MIP-SERS Biosensing Platform For The Detection Of Colorectal Cancer Marker NDKB

Early diagnosis of colorectal cancer(CRC)can greatly improve the overall survival of patients.Specific and sensitive detection of biomarkers is essential for early detection and dynamic monitoring of CRC.Nucleoside diphosphate kinase(NDK)is a nucleotide metabolizing enzyme transcribed and translated by the NME gene,and its family member NDKB protein(encoded by NME2)is an important marker for CRC diagnosis.However,current techniques used for NDKB screening have drawbacks such as high operational requirements,cumbersome procedures,and high costs.Surface Enhanced Raman Spectroscopy(SERS),as a spectroscopic analysis technique,has been used in different fields of research such as environmental monitoring,food health,pesticide residues,and tumor identification,with significant advantages such as nondamaging to samples,rapid detection,sensitive results,and specific peak shapes.However,in bioanalysis,the SERS technique still faces some challenges at this stage,such as the lack of reproducibility and stability of substrates,selective capture of target analytes,and how to resist matrix interference.In this paper,we designed and constructed a MIP-SERS biosensing platform for the first time to identify the colorectal cancer marker NDKB protein with high sensitivity and specificity.It provides a new reference method for molecular diagnosis and clinical screening of cancer patients,and the main research works are as follows:(1)We have explored the controlled synthesis and Raman performance of SERS active substrates.Based on the advantages of the high SERS activity of silver and the high stability of gold,we selected gold-core-silver-shell bimetallic nanoparticles(Au@Ag NPs)as SERS active substrates.The local surface plasmon resonance wavelength of the nanoparticles can be continuously changed by adjusting the thickness of the silver shell,which is capable of producing a strong SERS enhancement effect under a matching laser,and thus detecting very low concentrations of the target analytes.Using crystalline violet(CV)as the Raman reporter,the Au@Ag NPs with the best SERS activity were screened to achieve detection limits as low as 10-10 M and linear correlation in the range of 10-4 M～10-9 M,which can meet the sensitivity requirements for biological sample analysis.(2)We constructed and characterized a MIP-SERS biosensing platform based on SERS active substrates.Combining the characteristic capture selectivity of molecularly imprinted polymers(MIP)and the ultra-sensitivity of SERS technology,the sensing platform consists of an internal SERS active substrate Au@Ag NPs for signal enhancement and an external polydopamine(PDA)imprinted layer for NDKB recognition.Removal of NDKB from the imprinted layer creates spatially characterized and chemically functional imprinted cavities,which serve as the only access to the Raman reporter CV close to the SERS substrate,providing highly complementary structural sites for selective capture of NDKB based on ionic,hydrogen bonding or hydrophobic interactions.The specific recognition of NDKB would perfectly fill the imprinted cavity,which results in difficulty for the CV to approach the SERS substrate and a significant reduction of the Raman signal,while other substances cannot be matched.Therefore,the NDKB content can be indirectly reflected by the difference in the SERS signal.After characterizing the morphology,elemental composition,diffraction absorption,and functional group type of SERS substrate and PDA imprinted layer,the MIP-SERS biosensing platform was successfully constructed and can be used for further sensing performance optimization.(3)We optimized the sensing parameters associated with the MIP-SERS biosensing platform.To prepare the best-performing NDKB sensing platform,we optimized the corresponding sensing parameters of the platform based on the successful validation of the construction method in the previous chapter.Firstly,during the construction process,we screened the optimal mass ratio of NDKB and dopamine(DA)as 1:10,the optimal imprinting time as 9 h,and the optimal imprinting buffer as TrisHCl(pH 8.5).Secondly,for the actual detection,we screened the optimal concentration of Raman reporter CV as 0.1 mM and the optimal recognition time of NDKB as 15 min.Finally,the effects of CBBG and pH on the Raman signal were explored.After the optimization of all parameters,we finally obtained a MIP-SERS biosensing platform with excellent performance,which can be used for NDKB detection studies.(4)The detection performance of the MIP-SERS biosensing platform for NDKB was carried out.The optimal performance sensing platform was constructed using the best-optimized parameters,and the proposed sensing platform was able to achieve ultra-sensitive detection of NDKB by the variation of the Raman signal of CV molecules.A linear response was obtained over a broad series of ranges from 1 pg/mL to 1 mg/mL,achieving an ultra-low LOD of 0.82 pg/mL(0.47 fM)in serum samples.The specific recognition ability of the sensing platform was then investigated,and it was found that human/bovine serum albumin,pepsin/trypsin,and hemoglobin failed to induce significant changes in the SERS signal.Moreover,the sensing platform is resistant to matrix interference in water,simulated body fluids,and serum samples.In addition,the sensing process does not require the use of antibodies,which is cheaper;the reproducibility is good,with a low relative standard deviation of 30 random points;the stability is high,with only an 18%decrease in SERS intensity after 35 days;and the regeneration ability is high,with at least 5 reusable times.Thus,our constructed MIPSERS biosensing platform provides a nondestructive,rapid,quantitative,convenient,and economical means of detection.Thus,our proposed MIP-SERS biosensing platform has excellent sensitivity and high selectivity and is antibody-free,low-cost,low detection procedure,fast response time,able to be reused,biocompatible and stable,offering the potential for early diagnosis and prognostic assessment of colorectal cancer patients.In addition,our proposed method can be further extended to other biomarkers,which have potential applications in the early diagnosis and tumor progression prediction of cancer patients.